1. Data Representation using Graphs Hoang Dang

2. Motivation

3. Key Issue in Visualizing with Graph

4. Criteria for Aesthetic

5. Criteria for Aesthetic Cont…

6. Aesthetic is hard!

7. Algorithmic Approach Many approaches available! – Visibility representation – Upward planar testing – Spring algorithm

8. Visibility Representation

9. Upward Planar Testing

10. Spring Algorithm

11. Declarative Approach

12. Extreme VS Critical Mass

13. Findings of Metrics Paper All algorithms try to minimize crossings Grid based algorithms have high edge orthogonality Grid based generally perform better than spring based in symmetry

14. Graph Algorithm in My Project

15. Project Cont…

16. Conclusion Visualizing with a graph on large data set can be challenging Aesthetic is hard to achieve Many different algorithms provide aesthetics – Usually concern only a few criteria

17. References Helen C. Purchase. Metrics for graph drawing aesthetics. Journal of Visual Languages Computing, 501--516, 2002. Isabel F. Cruz and Roberto Tamassia. Tutorial on graph drawing, 2001.